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        <h1 id="绘制LV-0中的data列表数据"><a href="#绘制LV-0中的data列表数据" class="headerlink" title="绘制LV-0中的data列表数据"></a>绘制LV-0中的data列表数据</h1><h2 id="1-import-numpy-as-np"><a href="#1-import-numpy-as-np" class="headerlink" title="1. import numpy as np"></a>1. import numpy as np</h2><p>由于<strong>机器学习算法</strong>在数据处理过程中大都涉及线性代数的知识，需要用到<strong>矩阵操作</strong>，<strong>Python本身没有</strong>处理矩阵的数据类型，因此<strong>需要使用附加的函数库</strong>。</p>
<p><strong>NumPy函数库</strong>是Python开发环境的一个独立模块，是Python的一种<strong>开源的数值计算扩展</strong>工具。</p>
<p>这种工具可以用来<strong>存储和处理大型多维矩阵</strong>，比Python自身的列表结构要高效的多。尽管Python的list类型已经提供了类似于矩阵的表示形式，但是NumPy提供了更多的科学计算函数。</p>
<p>NumPy被定位为数学基础库，属于比较底层的Python库，其地位趋向于成为一个被其它库调用的核心库。</p>
<p>在使用NumPy库之前，首先必须导入该函数库，导入方式如下：<strong>import numpy as np</strong># import 模块名 as 别名</p>
<h2 id="2-matplotlib绘图"><a href="#2-matplotlib绘图" class="headerlink" title="2.matplotlib绘图"></a>2.matplotlib绘图</h2><p><strong>Matplotlib 是 Python 的绘图库</strong>。 它可与 <strong>NumPy 一起使用</strong>，提供了一种有效的 <strong>MatLab 开源替代</strong>方案。 它也可以和图形工具包一起使用，如 <strong>PyQt 和 wxPython</strong>。</p>
<p>Matplotlib 默认情况<strong>不支持中文</strong></p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment"># 为了显示中文，目的：标记横纵坐标</span></span><br><span class="line">pl.rcParams[<span class="string">&#x27;font.sans-serif&#x27;</span>]=[<span class="string">&#x27;SimHei&#x27;</span>]</span><br><span class="line">pl.rcParams[<span class="string">&#x27;axes.unicode_minus&#x27;</span>] = <span class="literal">False</span></span><br></pre></td></tr></table></figure>

<p>参考如下对matplotlib绘制的讲解</p>
<p><a target="_blank" rel="noopener" href="https://blog.csdn.net/gaotihong/article/details/80983937">https://blog.csdn.net/gaotihong/article/details/80983937</a></p>
<p><strong>pylab 是 matplotlib 面向对象绘图库的一个接口</strong>，它的语法和 <strong>Matlab</strong> 十分相近，主要的绘图命令和 Matlab 对应的命令有相似的参数</p>
<p>暂时不对Matplotlib进行了解，初步选用pylab函数。</p>
<h2 id="3-pylab和pyplot函数"><a href="#3-pylab和pyplot函数" class="headerlink" title="3.pylab和pyplot函数"></a>3.pylab和pyplot函数</h2><p><strong>pylab</strong> 模块是一款由python提供的可以绘制<strong>二维，三维数据</strong>的工具模块，其中包括了绘图软件包 matplotlib,其可以生成<strong>matab绘图库的图像。</strong> </p>
<p>pylab将<strong>所有的功能函</strong>数（<strong>pyplot状态机函数</strong>，大部分时numpy里面的函数）<strong>全部导入</strong>其单独的命名空间内。为什么要这样做，是因为这样可以很好地与ipython（或者类似的IDE，比如pycharm）实现很好的交互模式，这个就和MATLAB差不多。</p>
<p><strong>pylab和pyplot的区别是</strong>，<strong>前者将numpy导入了其命名空间中</strong>。这样会使pylab表现的和matlab更加相似。现在来说我们经常使用pyplot，因为pyplot相比pylab更加纯粹。</p>
<p>总结：使用的只是pylab里面的plot功能，暂时先直接使用pyplot函数。</p>
<p>matplotlib.pyplot：提供一个类似matlab的绘图框架。</p>
<p>pylab将pyplot与numpy合并为一个命名空间。这对于交互式工作很方便，但是对于编程来说，建议将名称空间分开.</p>
<h3 id="3-1-pyplot函数"><a href="#3-1-pyplot函数" class="headerlink" title="3.1 pyplot函数"></a>3.1 pyplot函数</h3><p>Matplotlib.pyplot 常用方法（一）:</p>
<p><a target="_blank" rel="noopener" href="https://blog.csdn.net/sinat_34022298/article/details/76348969">https://blog.csdn.net/sinat_34022298/article/details/76348969</a></p>
<p>绘图函数是直接作用于当前axes（matplotlib中的专有名词，图形中组成部分，不是数学中的坐标系。</p>
<p>重大发现：</p>
<p>为啥我的pycharm好多功能没有！！！！！！！！！</p>
<p>PyCharm 在<strong>2017.3版本</strong>之后加入了Scientific Mode</p>
<p>2019版社区版为啥很多功能没有呢，社区版这么不给力嘛。。。下载破解版</p>
<p>对电脑访问权限的更改，明日任务，菜鸡问题多呀</p>
<h2 id="总结"><a href="#总结" class="headerlink" title="总结"></a>总结</h2><p>就是问题一大堆，明天继续弄，速度过度到python</p>
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